Articles | Volume 9, issue 1
https://doi.org/10.5194/ascmo-9-67-2023
https://doi.org/10.5194/ascmo-9-67-2023
05 Jun 2023
 | 05 Jun 2023

Statistical modeling of the space–time relation between wind and significant wave height

Said Obakrim, Pierre Ailliot, Valérie Monbet, and Nicolas Raillard

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Cited articles

Accensi, M. and Maisondieu, C.: HOMERE. Ifremer Laboratoire Comportement des Structures en Mer, Ifremer Laboratoire Spatial et In terfaces Air Mer, [data set], https://doi.org/10.12770/cf47e08d-1455-4254-955e-d66225c9dc90, 2015. a
Anderson, D., Rueda, A., Cagigal, L., Antolinez, J., Mendez, F., and Ruggiero, P.: Time-varying emulator for short and long-term analysis of coastal flood hazard potential, J. Geophys. Res.-Oceans, 124, 9209–9234, 2019. a
Ardhuin, F. and Orfila, A.: Wind waves, New Frontiers in Operational Oceanography, 14, 393–422, 2018. a, b, c, d, e
Ardhuin, F., Hanafin, J., Quilfen, Y., Chapron, B., Queffeulou, P., Obrebski, M., Sienkiewicz, J., and Vandemark, D.: Calibration of the IOWAGA global wave hindcast (1991–2011) using ECMWF and CFSR winds, in: Proceedings of the 2011 International Workshop on Wave Hindcasting and Forecasting and 3rd Coastal Hazard Symposium, Kona, HI, USA, November 2014, vol. 30, 2011. a
Ardhuin, F., Stopa, J. E., Chapron, B., Collard, F., Husson, R., Jensen, R. E., Johannessen, J., Mouche, A., Passaro, M., Quartly, G. D., Swail, V., and Young, I.: Observing sea states, Front. Mar. Sci., 124, https://doi.org/10.3389/fmars.2019.00124, 2019. a
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Ocean wave climate has a significant impact on human activities, and its understanding is of socioeconomic and environmental importance. In this study, we propose a statistical model that predicts wave heights in a location in the Bay of Biscay. The proposed method allows us to understand the spatiotemporal relationship between wind and waves and predicts well both wind seas and swells.